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The Path to Net-Zero in Dairy Production: Are Pronounced Decreases in Enteric Methane Achievable?

2024· review· en· W4404398678 on OpenAlexaff
K. A. Beauchemin, E. Kebreab, Michelle Cain, M.J. VandeHaar

Bibliographic record

VenueAnnual Review of Animal Biosciences · 2024
Typereview
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsGreenhouse gasManureEnvironmental scienceAnaerobic digestionProduction (economics)Fossil fuelManure managementMethaneBiogasEnvironmental engineeringWaste managementAnimal scienceBiologyAgronomyEcologyEngineeringEconomics

Abstract

fetched live from OpenAlex

Achieving net-zero greenhouse gas (GHG) emissions in dairy production will require >50% reduction in enteric methane (CH 4 ) emissions together with elimination of emissions from feed production, additional carbon sequestration, reduction in manure emissions, anaerobic digestion of manure, and decreased reliance on fossil fuel energy. Over past decades, improved production efficiency has reduced GHG intensity of milk production (i.e., emissions per unit of milk) in the United States, but this trend can continue only if cows are bred for increased efficiency. Genetic selection of low-CH 4 -producing animals, diet reformulation, use of feed additives, and vaccination show tremendous potential for enteric CH 4 mitigation; however, few mitigation strategies are currently available, and added cost without increased revenue is a major barrier to implementation. Complete elimination of CH 4 emissions from dairying is likely not possible without negatively affecting milk production; thus, offsets and removals of other GHGs will be needed to achieve net-zero milk production.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.929
Threshold uncertainty score0.965

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.317
Teacher spread0.298 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2024
Admission routes1
Has abstractyes

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